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Full text of "Assessing urban forest effects and values : Minneapolis' urban forest"

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Do not assume content reflects current 
scientific knowledge, policies, or practices. 



A99.9 F7622Uf VSDA 



Assessing Urban Forest 

Foestse^ice Effects Bncl Values 

Northeastern 
Research Station 

Resource Bulletin NE-166 




Minneapolis' Urban Forest 




Abstract 

An analysis of trees in Minneapolis, MN, reveals that the city has about 979,000 trees with 
canopies that cover 26.4 percent of the area. The most common tree species are green ash, 
American elm, and boxelder. The urban forest currently stores about 250,000 tons of carbon 
valued at $4.6 million. In addition, these trees remove about 8,900 tons of carbon per year 
($164,000 per year) and trees and shrubs combined remove about 384 tons of air pollution 
per year ($1 .9 million per year). The structural, or compensatory, value is estimated at $756 
million. Information on the structure and functions of the urban forest can be used to improve 
and augment support for urban forest management programs and to integrate urban forests 
within plans to improve environmental quality in the Minneapolis area. 



The Authors 

DAVID J. NOWAK is a research forester and project leader, ROBERT E. HOEHN III, is a 
biological sciences technician, DANIEL E. CRANE is an information technology specialist, 
JACK C. STEVENS is a forester, and JEFFREY T WALTON is a research forester with 
the Forest Service's Northeastern Research Station at Syracuse, NY. JERRY BOND is a 
consulting urban forester and GREG INA is a manager of geographic information systems/ 
information technology with the Davey Resource Group at Kent, OH. 



Published by: For additional copies: 

USDA FOREST SERVICE USDA Forest Service 

1 1 CAMPUS BLVD SUITE 200 Publications Distribution 

NEWTOWN SQUARE PA 19073-3294 359 Main Road 

Delaware, OH 43015-8640 
May 2006 Fax: (740)368-01 52 



Visit our homepage at: http://www.fs.fed.us/ne 



Executive Summary 



Urban forests 
provide numerous 
benefits to society, 
yet relatively little 
is known about this 
important resource. 

In 2004, the UFORE 
model was used to 
survey and analyze 
Minneapolis' urban 
forest. 

The calculated 
environmental 
benefits of the 
Minneapolis 
urban forest 
are significant, 
yet many 

environmental and 
social benefits 
still remain to be 
quantified. 



Trees in cities can contribute significantly to human health and environmental quality. 
Unfortunately, little is known about the urban forest resource and what it contributes 
to the local and regional society and economy. To better understand the urban forest 
resource and its numerous values, the USDA Forest Service, Northeastern Research 
Station, developed the Urban Forest Effects (UFORE) model. Results from this model 
are used to advance the understanding of the urban forest resource, improve urban 
forest policies, planning and management, provide data for potential inclusion of trees 
within environmental regulations, and determine how trees affect the environment and 
consequently enhance human health and environmental quality in urban areas. 

Forest structure is a measure of various physical attributes of the vegetation, such as 
tree species composition, number of trees, tree density, tree health, leaf area, biomass, 
and species diversity. Forest functions, which are determined by forest structure, 
include a wide range of environmental and ecosystem services such as air pollution 
removal and cooler air temperatures. Forest values are an estimate of the economic 
worth of the various forest functions. 

To help determine the vegetation structure, functions, and values of the urban forest 
in Minneapolis, a vegetation assessment was conducted during the summer of 2004. 
For this assessment, one-tenth acre field plots were sampled and analyzed using the 
UFORE model. This report summarizes results and values of 

• Forest structure • Carbon storage 

• Risk of insect pests and diseases • Annual carbon removal (sequestration) 

• Air pollution removal • Changes in building energy use 

More detailed information can be found at: www.fs.fed.us/ne/syracuse/Data/data.htm. 



Minneapolis Urban Forest Summary 
Feature Measure 


Number of trees 


979,000 


Tree cover 


26.4% 


Most common species 


green ash, American elm. 




boxelder 


Percentage of trees 


47.3% 


< 6-inches diameter 




Pollution removal 


384 tons/year ($1.9 million/year) 


Carbon storage 


250,000 tons ($4.6 million) 


Carbon sequestration 


8,900 tons/year ($l64,000/year) 


BuUding energy reduction 


$2l6,000/year 


Avoided carbon emissions 


$l6,000/year 


Structural values 


$756 million 


Ton - short ton (U.S.) (2,000 lbs) 



1 




Urban Forest Effects Model 
and Field Measurements 

Though urban forests have many functions and values, currently only a few of these 
attributes can be assessed. To help assess the city's urban forest, data from 110 field 
plots located throughout the city were analyzed using the Forest Service's Urban Forest 
Effects (UFORE) model.' 



Benefits ascribed to 
urban trees include: 

• Air pollution 
removal 



• Air temperature 
reduction 

• Reduced building 
energy use 

• Absorption 
of ultraviolet 
radiation 

• Improved water 
quality 

• Reduced noise 

• Improved human 
comfort 

• Increased 
property value 

• Improved 
physiological & 
psychological 
well-being 

• Aesthetics 

• Community 
cohesion 



UFORE is designed to use standardized field data from randomly located plots and 
local hourly air pollution and meteorological data to quantify urban forest structure 
and its numerous effects, including: 

• Urban forest structure (e.g., species composition, tree density, tree health, leaf 
area, leaf and tree biomass, species diversity, etc.). 

• Amount of pollution removed hourly by the urban forest and its associated 
percent air quality improvement throughout a year. Pollution removal is 
calculated for ozone, sulfur dioxide, nitrogen dioxide, carbon monoxide and 
particulate matter (<10 microns). 

• Total carbon stored and net carbon annually sequestered by the urban forest. 

• Effects of trees on energy use in buildings and consequent effects on carbon 
dioxide emissions from power plants. 

• Compensatory value of the forest, as well as the value for air pollution removal 
and carbon storage and sequestration. 

• Potential impact of infestations by Asian longhorned beetles, emerald ash 
borers, gypsy moth, and Dutch elm disease. 

For more information go to http://www.ufore.org 



In the field, one-tenth acre plots were randomly located within a grid pattern at a 
density of approximately one plot every 340 acres. In Minneapolis, service districts 
were used to divide the analysis into smaller 
zones. The plots were divided among the 
following service districts: River District 
(49 plots). Lakes District (31 plots), and 
Minnehaha District (30 plots). 



Study Area 




2 



Field Survey Data 
Plot Information 

• Land use type 

• Percent tree cover 

• Percent shrub 
cover 

• Percent plantable 

• Percent ground 
cover types 

• Shrub species / 
dimensions 

Tree parameters 

• Species 

• Stem diameter 

• Total height 

• Height to crown 
base 

• Crown width 

• Percent foliage 
missing 

• Percent dieback 

• Crown light 
exposure 

• Distance and 
direction to 
buildings from 
trees 



Field data were collected by Davey Resource Group during the leaf-on season to 
properly assess tree canopies. Within each plot, data included land use, ground and 
tree cover, shrub characteristics, and individual tree attributes of species, stem diameter 
at breast height (d.b.h.; measured at 4.5 ft), tree height, height to base of live crown, 
crown width, percentage crown canopy missing and dieback, and distance and 
direction to residential buildings. - 

To calculate current carbon storage, biomass for each tree was calculated using 
equations from the literature and measured tree data. Open-grown, maintained trees 
tend to have less biomass than predicted by forest-derived biomass equations.-^ To 
adjust for this difference, biomass results for open-grown urban trees are multiplied by 
0.8.^ No adjustment is made for trees found in natural stand conditions. Tree dry- 
weight biomass was converted to stored carbon by multiplying by 0.5. 

To estimate the gross amount of carbon sequestered annually, average diameter growth 
from the appropriate genera and diameter class and tree condition was added to the 
existing tree diameter (year x) to estimate tree diameter and carbon storage in year x+ 1 . 

Air pollution removal estimates are derived from calculated hourly tree-canopy 
resistances for ozone, and sulfur and nitrogen dioxides based on a hybrid of big-leaf 
and multi-layer canopy deposition models.^'^ As the removal of carbon monoxide 
and particulate matter by vegetation is not directly 
related to transpiration, removal rates (deposition 
velocities) for these pollutants were based on 
average measured values from the literature^'^ that 
were adjusted depending on leaf phenology and 
leaf area. Particulate removal incorporated a 50 
percent resuspension rate of particles back to the 
atmosphere.^ 

Seasonal effects of trees on energy use in residential 
building was calculated based on procedures 
described the literature^ using distance and direction 
of trees from residential structures, tree height and 
tree condition data. 

Compensatory values were based on valuation 
procedures of the Council of Tree and Landscape 
Appraisers, which uses tree species, diameter, conditii 

To learn more about UFORE methods" visit: 
http://www.fs.fed.us/ne/syracuse/Data/data.htm or www.ufore.org 




3 



Tree Characteristics of the Urban Forest 



There are an 
estimated 979,000 
trees in IVIinneapolis 
with canopies that 
cover 26.4 percent 
of the city. 

The 10 most 
common species 
account for 75 
percent of the total 
number of trees. 



The urban forest of Minneapolis has an estimated 979,000 trees and a tree cover of 
26.4 percent. Trees with diameters less than 6 inches account for 47.3 percent of the 
population. The three most common species are green ash (21.6 percent), American 
elm (17.1 percent), and boxelder (9.1 percent). The 10 most common species account 
for 75 percent of all trees; their relative abundance is illustrated below. 




Tree density is 
highest in the Lakes 
District, lowest in 
the River District. 



The highest density of trees occurs in the Lakes District (31.6 trees/acre), followed by 
the Minnehaha District (29.0 trees/acre) and the River District (19.8 trees/acre). The 
overall tree density in Minneapolis is 26.2 trees/acre, which is within the range of other 
city tree densities (Appendix I), of 14.4 to 119.2 trees/acre. 




4 




Nearly three- 
quarters of the 
tree species in 
Minneapolis are 
native to Minnesota. 

Urban forests are 
a mix of native 
tree species that 
existed prior to the 
development of 
the city and exotic 
species that were 
introduced by 
residents or other 
means. 




<^ 'i> 

d.b.h. class 



Urban forests are a mix of native trees species that existed prior to the development 
of the city and exotic species that were introduced by residents or other means. 
Thus, urban forests often have a tree diversity that is higher than surrounding native 
landscapes. An increased tree diversity can minimize the overall impact or destruction 
by a species-specific insect or disease, but the increase in the number of exotic plants 
can also pose a risk to native plants if some of the exotics species are invasive plants 
that can potentially out-compete and displace native species. In Minneapolis, about 
80 percent of the trees are species native to North America, while 74 percent are native 
to the state. Species exotic to Minnesota make up 26 percent of the population. Most 
exotic tree species have an origin from Eurasia (9.2 percent of the species). 



100 n 
90 - 




*North America + refers to tree species that are native to North America and one other continent. 



5 




Urban Forest Cover and Leaf Area 

Trees cover about 26.4 percent of Minneapolis and shrubs cover 6 percent of the city. 
Dominant ground cover types include herbaceous (e.g., grass, gardens) (34.0 percent), 
impervious surfaces (excluding buildings) (e.g., driveways, sidewalks, parking lots) 
(33.6 percent), and buildings (18.0 percent). 



Healthy leaf area 
equates directly 
to tree benefits 
provided to the 
community. 

Green ash has the 
greatest importance 
to the IVIinneapolis 
urban forest based 
on relative leaf 
area and relative 
population. 



Common 


% 


% 




Name 


Pop'' 


LA'' 




green ash 


21.6 


24.8 


46.4 


American 


17.1 


16.1 


33.2 


elm 








silver maple 


3.3 


10.5 


13.8 


Norway 


4.2 


7.6 


11.8 


maple 








boxelder 


9.1 


1.4 


10.5 


northern 


4.3 


4.0 


8.3 


hackberry 








bur oak 


1.9 


5.4 


7.3 


white 


4.3 


1.2 


5.5 


mulberry 








northern 


4.8 


0.9 


5.7 


white cedar 









^Percent population 
'^Percent leaf area 

^Importance value (%Pop + %LA) 



Minneapolis 
Minnehaha District 
Lakes District 
River District 




I water 
I bare soil 
I herbaceous 



duff/mulch cover 

I impervious surfaces (excluding buildings) 
■ buildings 



Many tree benefits are linked directly to the amount of healthy leaf surface area of 
the plant. In Minneapolis, trees that dominate in terms of leaf area are green ash, 
American elm, and silver maple. 

Tree species with relatively large individuals contributing leaf area to the population 
(species with percentage of canopy much greater than percentage of population) are 
silver maple, bur oak, and sugar maple. Smaller trees in the population are American 
basswood, northern white cedar, and boxelder (species with percentage of canopy 
much less than percentage of population). A species must also constitute at least 1 
percent of the total population to be considered as relatively large or small trees in the 
population. 

Tree importance values (IV) are calculated using a formula that takes into account the 
relative leaf area and relative composition. The most important species in the urban 
forest, according to calculated IVs, are green ash, 7\merican elm, and silver maple. 



25 n 



20 



15 - 



10 



% of total leaf area 
I % of all trees 




The urban forest 
of Minneapolis 
removes about 384 
tons of pollutants 
each year, with a 
value to society of 
$1.9 million/year. 

General urban 
forest management 
recommendations 
to improve air 
quality are given in 
Appendix II. 



Air Pollution Removal by Urban Trees 

Poor air quality is a common problem in many urban areas. It can lead to human 
health problems, damage to landscape materials and ecosystem processes, and reduced 
visibility. The urban forest can help improve air quality by reducing air temperature, 
directly removing pollutants from the air, and reducing energy consumption in 
buildings, which consequently reduce air pollutant emissions from power plants. 
Trees also emit volatile organic compounds that can contribute to ozone formation. 
However, integrative studies have revealed that an increase in tree cover leads to 
reduced ozone formation.'- 

Pollution removal by trees and shrubs in Minneapolis was estimated using field data 
and hourly pollution and weather data for 2000. Pollution removal was greatest for 
particulate matter less than ten microns (PM^^j), followed by ozone (O^), nitrogen 
dioxide (NOJ, sulfur dioxide (SOJ, and carbon monoxide (CO). It is estimated that 
trees and shrubs remove 384 tons of air pollution (CO, NO,, O^, PM^^, SO J per 
year with an associated value of $1.9 million (based on estimated national median 
externality costs associated with pollutants'-'). Trees remove about four times more air 
pollution than shrubs in Minneapolis. 

The average percentage of air pollution removal during the daytime, in-leaf season was 
estimated to be: 



O3 
PM, 

SO, 



0.58% 
0.57% 
0.57% 



NO, 
CO 



0.36% 
0.002% 



Peak 1-hour air quality improvements during the in-leaf season for heavily-treed areas 
(100% tree cover) was estimated to be: 



O3 
PM, 

SO, 



14.9% 
11.1% 
15.5% 



• NO, 

• CO 



7.2% 
0.05% 



160 

140 

»" 120 

c 

o 

^"100 



■ Pollution Removed 
— Value (U.S. Dollars) 




7 




Carbon storage: 

Carbon currently 
held In tree tissue 
(roots, stems, and 
branches). 

Carbon 
sequestration: 

Estimated amount 
of carbon removed 
annually by 
trees. Net carbon 
sequestration 
can be negative If 
emission of carbon 
from decomposition 
Is greater than 
amount sequestered 
by healthy trees. 



Carbon Storage and Sequestration 

Climate change is an issue of global concern. Urban trees can help mitigate climate 
change by sequestering atmospheric carbon (from carbon dioxide) in tissue and by 
reducing energy use in buildings, consequently reducing carbon dioxide emissions 
from fossil-fuel based power plants.'^ 



Trees reduce the amount of carbon in the atmosphere by sequestering carbon in new 
tissue growth every year. The amount of carbon annually sequestered is increased 
with healthier trees and larger diameter trees. Minneapolis' trees gross sequestration is 
about 8,900 tons of carbon per year with an associated value of $164,000. Net carbon 
sequestration in the Minneapolis urban forest is about 4,200 tons. 



1 ,800 n 
1,600 




llllllll 



32,000 
27,000 
22,000 % 
- 17,000 ■§ 
12,000 2. 



7,000 ra 
> 

2,000 
-3,000 



<? <? cj 



<9 & > 

C) (7) ^7* 



Carbon storage by trees is another way trees can influence global climate change. As 
trees grow, they store more carbon by holding it in their accumulated tissue. As trees 
die and decay, they release much of the stored carbon back into the atmosphere. Thus, 
carbon storage is an indication of the amount of carbon that can be lost if trees are 
allowed to die and decompose. Trees in Minneapolis are estimated to store 250,000 
tons of carbon ($4.6 million). Of all the species sampled, American elm stores and 
sequesters the most carbon (about 18.6 percent of the total carbon stored and 19.2 
percent of all sequestered carbon). 



120,000 

100,000 

-Ij- 80.000 
c 
o 

o 
ra 
o 

55 40,000 
20,000 



■i Carbon Storage 

-*- Carbon Sequestration 




2,500 



2,000 



1,500" 



1,000 S 



500 



d.b.h. class 



8 




Trees affect energy 
consumption by 
shading buildings, 
providing | 
evaporative cooling,! 
and blocking winter | 
winds. 

Interactions 
between buildings | 
and trees save an j 
estimated $221,000 \ 
in heating and ; 
cooling costs. 

Lower energy use ini 
residential buildingsi 
reduced carbon i 
emissions from 
power plants by 900 
tons ($15,900). 



Trees Affect Energy Use in Buildings 

Trees affect energy consumption by shading buildings, providing evaporative cooling, 
and blocking vi^inter winds. Trees tend to reduce building energy consumption in the 
summer months and can either increase or decrease building energy use in the winter 
months, depending on the location of trees around the building. Estimates of tree 
effects on energy use are based on field measurements of tree distance and direction to 
space-conditioned residential buildings.^ 

Based on 2002 energy costs, trees in Minneapolis are estimated to reduce energy costs 
from residential buildings by $221,000 annually. Trees also provide an additional 
$15,900 in value by reducing the amount of carbon released by fossil-fuel based power 
plants (a reduction of 900 tons of carbon emissions). 



Annual energy savings due to trees near residential buildings. Note: 
negative numbers indicate an increase in energy use or carbon emissions. 





Heating 


Cooling 


Total 


MBTU^' 


-174,000 


n/a 


-174,000 


MWRb 


-1,100 


17,900 


16,800 


Carbon avoided (t) 


-3,100 


4,000 


900 



''Million British Thermal Units 
''Megawatt-hour 



Annual savings'^ (U.S. $) in residential energy expenditure during 
heating and cooling seasons. Note: negative numbers indicate a cost 
due to increased energy use or carbon emissions. 





Heating 


Cooling 


Total 


MBTU^ 


-1,182,000 


n/a 


-1,182,000 


MWRb 


-96,000 


1,499,000 


1,403,000 


Carbon avoided 


-57,500 


73,400 


15,900 



^Million British Thermal Units 

''Megawatt-hour 

■^Based on state-wide energy cost 



9 



structural and Functional Values 

Urban forests have a structural value based on the tree itself (e.g., the cost of having 
to replace the tree with a similar tree). The structural value'° of urban forest in 
Minneapolis is about $756 million. The structural value of an urban forest tends to 
increase with a rise in the number and size of healthy trees. 



Urban forests have 
a structural value 
based on the tree 
itself. 

Urban forests also 
have functional 
values based on the 
functions the tree 
performs. 

Large, healthy, 
long-lived trees 
provide the greatest 
structural and 
functional values. 



Urban forests also have functional values (either positive or negative) based on the 
functions the tree performs. Annual functional values also tend to increase with 
increased number and size of healthy trees, and are usually on the order of several 
million dollars per year. There are many other functional values of the urban forest, 
though they are not quantified here (e.g., reduction in air temperatures and ultra- 
violet radiation, improvements in water quality). Through proper management, urban 
forest values can be increased. However, the values and benefits also can decrease as the 
amount of healthy tree cover declines. 

Structural values: 

• Structural value: $756 million 

• Carbon storage: $4.6 million 

Annual functional values: 

• Carbon sequestration: $164,000 

• Pollution removal: $1.9 million 

• Lower energy costs and carbon emission reductions: $237,000 

More detailed information on the urban forest in Minneapolis can be found at www. 
fs.fed.us/ne/syracuse/Data/data.htm. Additionally, information on other urban 
forest values can be found in Appendix I and information comparing tree benefits to 
estimates of average carbons emissions in the city, average automobile emissions, and 
average household emissions can be found in Appendix III. 




10 



Asian longhorned 
beetle 




David Cappaert 
Michigan State University 
(www.invasive.org) „ 



Gypsy moth 





USDA Forest Service Archives 
(www.invasive.org) 



Potential Insect and Disease Impacts 

Various insects and diseases can infest urban forests, potentially killing trees and 
reducing the health, value and sustainability of the urban forest. As various pests have 
differing tree hosts, the potential damage or risk of each pest will differ. Four exotic 
pests w^ere analyzed for their potential impact: Asian longhorned beetle, gypsy moth, 
emerald ash borer, and Dutch elm disease. 

The Asian longhorned beetle (ALB)'' is an insect that bores into and kills a wide range 
of hardwood species. ALB represents a potential loss to the Minneapolis urban forest 
of $487 million in structural value (68.1 percent of the tree population). 




ALB 



GM 



EAB 



DED 



The gypsy moth (GM)"^ is a defoliator that feeds on many species causing widespread 
defoliation and tree death if outbreak conditions last several years. This pest could 
potentially result in a loss of $80 million in structural value (10.1 percent of the tree 
population). 



Emerald ash borer (EAB)''' has killed thousands of ash trees in Michigan, Ohio, and 
Indiana. EAB has the potential to affect 22.0 percent of the population ($148 million 
in structural value). 



American elm, one of the most important street trees in the 20th century, has been 
devastated by the Dutch elm disease (DED). Since first reported in the 1930s, it 
has killed more than 50 percent of the native elm population in the United States.'^ 
Although some elm species have shown varying degrees of resistance, Minneapolis 
possibly could lose 17.1 percent of its trees to this disease ($l4l million in structural 
value) . 



11 



Appendix I. Comparison of Urban Forests 



A commonly asked question is, "How does this city compare to other cities?" Although comparison among 
cities should be made with caution as there are many attributes of a city that affect urban forest structure and 
functions, summary data are provided from other cities analyzed using the UFORE model. 



I. City totals, trees only 











Carbon 


Pollution 






^/o 'Free 








rpm 1 


l^ol Ti 1 f"!r\n A/o 1 n^^ 
1 L/11U.LHJI1 VdlU-C 


Citv 


cover 


Number of trees 


Storage (tons) 


(tons/yr) 


(tons/yr) 


U.S. $ 


(^aJgary, Canada 




1 i>ooy,UUU 


/ / c c\r\c\ 


1 / r\r\ 




1 /" 1 1 AAA 

l,ol 1,000 


Atlanta, kjA 


JO./ 


O / 1 C f\f\f\ 


1 "XAA (\C\C\ 

1,:744,UUU 


/if A f\C\ 
4o,4UU 




o 2 T 1 AAA 
0,321,000 


loronto, L^anaua 


zUo 


/,D4z,UUU 


OOT C\C\C\ 


/A 'XC\C\ 




r 1 AC AAA 

o, 105,000 


Npw York MY^" 






1 ^SO 000 


47 ^00 


1)0/ / 


0,U/ i ,UUv/ 


Ralrimnrp K/TD'* 


21.0 


1 COl 000 


SQ7 000 


ir^ 700 


4^0 


V^J ■y\j\j\j 


Philadelphia, PA'' 


15.7 


2,113,000 


530,000 


16,100 


576 


2,826,000 


Washington, DO 


28.6 


1,928,000 


523,000 


16,100 


418 


1,956,000 


Boston, MA'' 


22.3 


1,183,000 


319,000 


10,500 


284 


1,426,000 


Woodbridge, NJ^ 


29.5 


986,000 


160,000 


5,560 


210 


1,037,000 


Minneapolis, MN? 


26.4 


979,000 


250,000 


8,900 


306 


1,527,000 


Syracuse, NY* 


23.1 


876,000 


173,000 


5,420 


109 


568,000 


San Francisco, CA^ 


11.9 


668,000 


194,000 


5,100 


141 


693,000 


Morgantown, WV'' 


35.5 


658,000 


93,000 


2,890 


72 


333,000 


Moorestown, NJ^ 


28.0 


583,000 


117,000 


3,760 


118 


576,000 


Jersey City, NJ^ 


11.5 


136,000 


21,000 


890 


41 


196,000 


Freehold, NJ*' 


34.4 


48,000 


20,000 


545 


22 


110,000 



II. Per acre values of tree effects 







Carbon Stora^ 


^e Carbon sequestration Poll 


ution removal 


Pollution value 


City 


No. of trees 


(tons) 


(tons/yr) 


(Ibs/yr) 


U.S. $ 


Calgary, Canada^ 


66.7 


2.5 


0.12 


3.7 


9.0 


Atlanta, GA'' 


111.6 


15.9 


0.55 


39.4 


98.6 


Toronto, Canada^ 


48.3 


6.4 


0.26 


15.5 


39.1 


New York, NY*' 


26.4 


6.8 


0.21 


17.0 


40.9 


Baldmore, MD** 


50.8 


11.6 


0.31 


16.6 


41.2 


Philadelphia, PA*" 


25.1 


6.3 


0.19 


13.6 


33.5 


Washington, DC= 


49.0 


13.3 


0.41 


21.3 


49.7 


Boston, MA'' 


33.5 


9.1 


0.30 


16.1 


40.4 


Woodbridge, Njf 


66.5 


10.8 


0.38 


28.4 


70.0 


Minneapolis, MNs 


26.2 


6.7 


0.24 


16.4 


40.9 


Syracuse, iW 


54.5 


10.8 


0.34 


13.5 


35.4 


San Francisco, CA* 


22.5 


6.6 


0.17 


9.5 


23.4 


Morgantown, WV'' 


119.2 


16.8 


0.52 


26.0 


60.3 


Moorestown, NJ^ 


62.1 


12.4 


0.40 


25.1 


61.3 


Jersey City, NJ*^ 


14.4 


2.2 


0.09 


8.6 


20.7 


Freehold, Njf 


38.3 


16.0 


0.44 


34.9 


88.2 


Data collection group 












^ City personnel 






' Casey Trees Endowment Fund 






''ACRT, Inc. 






^ New Jersey Department of Environmental Protect! 


ion 


University of Toronto 






8 Davey Resource Group 






^ U.S. Forest Service 






West Virginia University 







12 



Appendix II. General Recommendations for Air Quality Improvement 

Urban vegetation can directly and indirectly affect local and regional air quality by altering the urban atmospheric 
environment. Four main ways that urban trees affect air quality are: 

Temperature reduction and other microclimatic effects 
Removal of air pollutants 

Emission of volatile organic compounds (VOC) and tree maintenance emissions 
Energy conservation in buildings and consequent power plant emissions 

The cumulative and interactive effects of trees on climate, pollution removal, and VOC and power plant emissions 
determine the overall impact of trees on air pollution. Cumulative studies involving urban tree impacts on ozone 
have revealed that increased urban canopy cover, particularly with low VOC emitting species, leads to reduced ozone 
concentrations in cities. Local urban forest management decisions also can help improve air quality. 



Urban forest management strategies to help improve 

Strategy 



air quality include: 

Reason 



Increase the number of healthy trees 

Sustain existing tree cover 

Maximize use of low VOC-emitting trees 

Sustain large, healthy trees 

Use long-lived trees 

Use low maintenance trees 

Reduce fossil fuel use in maintaining vegetation 

Plant trees in energy conserving locations 

Plant trees to shade parked cars 

Supply ample water to vegetation 

Plant trees in polluted or heavily populated areas 

Avoid pollutant-sensitive species 

Utilize evergreen trees for particulate matter 



Increase pollution removal 

Maintain pollution removal levels 

Reduces ozone and carbon monoxide formation 

Large trees have greatest per-tree effects 

Reduce long-term pollutant emissions from planting and removal 

Reduce pollutants emissions from maintenance activities 

Reduce pollutant emissions 

Reduce pollutant emissions from power plants 

Reduce vehicular VOC emissions 

Enhance pollution removal and temperature reduction 

Maximizes tree air quality benefits 

Improve tree health 

Year-round removal of particles 




13 



Appendix III. Relative Tree Effects 

The urban forest in Minneapohs provides benefits that include carbon storage and sequestration, and air pollutant 
removal. To estimate a relative value of these benefits, tree benefits were compared to estimates of average carbon 
emissions in city^^, average passenger automobile emissions-*^, and average household emissions.^' 

General tree information: 

Average tree diameter (d.b.h.) = 10.3 in. 
Median tree diameter (d.b.h.) = 6.7 in. 
Average number of trees per person = 2.6 
Number of trees sampled = 278 
Number of species sampled = 41 



Average tree effects by tree diameter: 



Pollution 





Carbon stora^ 




Carbon 


sequestration 


removal 


D.b.h. 

Class (inch) 


(lbs) 


($) 


(miles)'' 


(Ibs/yr) 


($/yr) 


(miles)^ 


(lbs) 


($) 


1-3 


8 


0.08 


30 


2.4 


0.02 


9 


0.4 


0.86 


3-6 


44 


0.40 


160 


6.2 


0.06 


23 


0.4 


0.95 


6-9 


124 


1.15 


460 


12.0 


0.11 


44 


0.6 


1.34 


9-12 


268 


2.47 


980 


18.7 


0.17 


69 


0.8 


1.86 


12-15 


483 


4.45 


1,770 


24.5 


0.23 


90 


0.8 


1.81 


15-18 


721 


6.64 


2,640 


30.3 


0.28 


111 


0.9 


2.01 


18-21 


1,068 


9.84 


3,910 


37.7 


0.35 


138 


0.8 


1.84 


21-24 


1,303 


12.00 


4,770 


40.7 


0.37 


149 


0.9 


1.99 


24-27 


1,516 


13.97 


5,550 


31.4 


0.29 


115 


1.7 


3.75 


27-30 


2,883 


26.55 


10,560 


75.3 


0.69 


276 


0.7 


1.69 


30+ 


4,338 


39.96 


15,890 


91.2 


0.84 


334 


1.1 


2.51 


" miles = numbi 


er of automobi 


le miles driven that p 


reduces emissions equivaJ 


lent to 


tree effect 







The Minneapolis urban forest provides: 

Carbon storage equivalent to: 

Amount of carbon (C) emitted in city in 40 days or 
Annual C emissions from 150,000 automobiles or 
Annual C emissions from 75,500 single family houses 

Carbon monoxide removal equivalent to: 

Annual carbon monoxide emissions from 31 automobiles or 

Annual carbon monoxide emissions from 100 single family 

houses 

Nitrogen dioxide removal equivalent to: 

Annual nitrogen dioxide emissions from 2,900 automobiles or 
Annual nitrogen dioxide emissions from 1,900 single family 
houses 



Sulfur dioxide removal equivalent to: 

Annual sulfur dioxide emissions from 19,900 automobiles or 
Annual sulfur dioxide emissions from 300 single family houses 



Particulate matter less than 10 micron (PM ^ ^) removal 



equivalent to: 

Annual PMIO emissions from 315,600 automobiles or 
Annual PMIO emissions from 30,500 single family houses 

Annual C sequestration equivalent to: 
Amount of C emitted in cit}' in 1 .4 days or 
Annual C emissions from 5,300 automobiles or 
Annual C emissions from 2,700 single family homes 



14 



Appendix IV. List of Species Sampled in Minneapolis 



Potential pest ^ 



Genus 


Species 


Common Name 


% Population 


% Leaf Area 




ALB 


GM 


Abies 


concolor 


white fir 


0.3 


0.9 


1.2 






Acer 


negundo 


boxelder 


9.1 


1.4 


10.5 






Acer 


platanoides 


Norway maple 


4.2 


7.6 


11.8 






Acer 


saccharinum 


silver maple 


3.3 


10.5 


13.8 


k 




Acer 


saccharum 


sugar maple 


1.0 


3.5 


4.5 


k 




Acer 


rubrum 


red maple 


1.0 


1.0 


2.0 


A 




Aesculus 


pavia 


red buckeye 


0.4 


1.2 


1.6 






Aesculus 


hippocastanum 


horsechestnut 


0.3 


0.4 


0.7 






Betula 






1 . 1 


1.4 


2 5 




A 


Detuia 


pendula 


European white birch 


U.D 


u.z 


U.o 


A 


-% 


Catalpa 


speciosa 


northern catalpa 


0.7 


1.2 


1.9 






Celtis 


occidentalis 


northern hackberry 


4.3 


4.0 


8.3 






rraxinus 


pennsylvanica 


green ash 


zl.o 


24. o 


46.4 


4- 




Lrleditsia 


triacanthos 


honeylocust 


2.2 


1.3 


3.5 






Juglans 


nigra 


black walnut 


0.9 


0.2 


1.1 






Juniperus 


species 


juniper 


0.3 


0.5 


0.8 






Malus 


species 


1 1 

crabapple 


2.6 


0.8 


3.4 






Morus 


alba 


white mulberry 


4.3 


1.2 


5.5 






Other 


species 


other species 


0.9 


0.3 


1.2 






Picea 


pungens 


blue spruce 


3.3 


1.9 


5.2 






Picea 


glauca 


white spruce 


1.4 


1.4 


2.8 






Pinus 


nigra 


Austrian pine 


2.6 


3.1 


5.7 






Pinus 


strobus 


eastern white pine 


u. / 


yj.o 








Pinus 


resi nosa 




0.4 


0.7 


1.1 






Pinus 


^vlvp^rri^ 

jy 1 V Ll lo 




0.4 


0.1 


5 






Populus 


nigra 


black poplar 


0.6 


0.1 


0.7 






Populus 


balsamifera 


balsam poplar 


0.4 


0.0 


0.4 






Populus 


deltoides 


eastern cottonwood 


0.3 


0.2 


0.5 






Prunus 


serrulata 


Kwanzan cherry 


0.8 


0.1 


0.9 


4 




Prunus 


serotina 


black cherry 


0.4 


0.0 


0.4 


4 





Continued 



15 



Appendix IV continued. 

















rotentiai pest 


Lrcnus 


opecies 


L-ommon IName 


% Population 


To Lear Area 


IV 




<jM hAJb JJhJJ 


Prunus 


X cistena 


purpieiear sand cherry 


0.4 


0.0 


0.4 






rseudotsu^ 


^a menziesii 


dougias hr 


0.4 


0.3 


0.7 






Quercus 


macrocarpa 


bur oak 


1.9 


5.4 


7.3 






Quercus 


alba 


white oak 


0.4 


1.1 


1.5 




4^ 


Quercus 


rubra 


northern red oak 


0.4 


0.1 


0.5 


A 




Sorbus 


aucuparia 


European mountain 
ash 


0.4 


0.1 


0.5 






■ 

i nu)a 


occidentalis 


northern white cedar 






S 7 
J./ 






Tilia 

1 Hid 








9 


1 






Tilia 


cordata 


littleleaf linden 


1.0 


1.6 


2.6 






Ulmus 


americana 


American elm 


17.1 


16.1 


33.2 






Ulmus 


pumila 


Siberian elm 


1.7 


3.3 


5.0 


4 





""IV = importance value (% population + % leaf area) 

''ALB = Asian longhorned beetle; GM = g}'psy moth; EAB = emerald ash borer; DED = Dutch elm disease 




16 



References 

1 Nowak, D.J.; Crane, D.E. 2000. The Urban Forest 

Effects (UFORE) Model: quantiiying urban 
forest structure and functions. In: Hansen, M.; 
Burk, T., eds. Integrated tools for natural resources 
inventories in the 21st century. Proceedings of 
lUFRO conference. Gen. Tech. Rep. NC-212. St. 
Paul, MN: U.S. Department of Agriculture, Forest 
Service, North Central Research Station: 714-720. 

2 Nowak, D.J.; Crane, D.E.; Stevens, J.C.; Hoehn, R.E. 

2005. The urban forest effects (UFORE) modeh 
field data collection manual. VI b. [Nev^aown 
Square, PA]: U.S. Department of Agriculture, 
Forest Service, Northeastern Research Station. 34 p. 
http : //www. fs .fed. us/ ne/ syracuse/Tools/ downloads/ 
UFORE_Manual.pdf 

3 Nowak, D.J. 1994. Atmospheric carbon dioxide 

reduction by Chicago's urban forest. In: 

McPherson, E.G.; Nowak, D.J.; Rowntree, R.A., 
eds. Chicago's urban forest ecosystem: results of 
the Chicago Urban Forest Climate Project. Gen. 
Tech. Rep. NE-186. Radnor, PA: U.S. Department 
of Agriculture, Forest Service, Northeastern Forest 
Experiment Station: 83-94. 

4 Baldocchi, D. 1988. A multi-layer model for 

estimating sulfur dioxide deposition to a 
deciduous oak forest canopy. Atmospheric 
Environment. 22: 869-884. 

5 Baldocchi, D.D.; Hicks, B.B.; Camara, P 1987. A 

canopy stomatal resistance model for gaseous 
deposition to vegetated surfaces. Atmospheric 
Environment. 21: 91-101. 

6 Bidwell, R.G.S.; Fraser, D.E. 1972. Carbon 

monoxide uptake and metabolism by leaves. 

Canadian Journal of Botany. 50: 1435-1439. 

7 Lovett, G.M. 1994. Atmospheric deposition of 

nutrients and pollutants in North America: an 



ecological perspective. Ecological Applications. 4: 
629-650. 

8 Zinke, P.J. 1967. Forest interception studies in the 

United States. In: Sopper, W.E.; Lull, H.W., eds. 
Forest hydrology. Oxford, UK: Pergamon Press: 
137-161. 

9 McPherson, E.G.; Simpson, J. R. 1999. Carbon 

dioxide reduction through urban forestry: 
guidelines for professional and volunteer tree 
planters. Gen. Tech. Rep. PSW-171. Albany, CA: 
U.S. Department of Agriculture, Forest Service, 
Pacific Southwest Research Station. 237 p. Can 
be accessed through http://www.fs.fed.us/psw/ 
publications/gtrs.shtml 

10 Nowak, D.J.; Crane, D.E.; Dwyer, J.E 2002. 
Compensatory value of urban trees in the United 
States. Journal of Arboriculture. 28(4): 194-199. 

1 1 Nowak, D.J.; Crane, D.E.; Stevens, J.C.; Ibarra, M. 
2002. Brooklyn's urban forest. Gen. Tech. Rep. 
NE-290. Newtown Square, PA: U.S. Department of 
Agriculture, Forest Service, Northeastern Research 
Station. 107 p. 

12 Nowak D.J.; Dwyer, J.E 2000. Understanding 
the benefits and costs of urban forest ecosystems. 

In: Kuser, John E., ed. Handbook of urban and 
community forestry in the northeast. New York: 
Kluwer Academics/Plenum: 1 1-22. 

13 Murray, F.J.; Marsh L.; Bradford, PA. 1994. New 
York state energy plan, vol. II: issue reports. 

Albany, NY: New York State Energy Office. 

14 Abdollahi, K.K.; Ning, Z.H.; Appeaning, A., eds. 
2000. Global climate change and the urban 
forest. Baton Rouge, LA: GCRCC and Franklin 
Press. 77 p. 

1 5 Northeastern Area State and Private Forestry. 2005. 
Asian Longhomed Beetle. Newtown Square, PA: 



17 



U.S. Department of Agriculture, Northeastern Area 
State and Private Forestry, http://www.na.fs.fed. 
us/fhp/alb/ 

16 Northeastern Area State and Private Forestry. 
2005. Gypsy moth digest. Newtown Square, PA: 
U.S. Department of Agriculture, Forest Service, 
Northeastern Area State and Private Forestry. 
http://wvvw.na.fs.fed.us/fhp/gm/ 

17 Northeastern Area State and Private Forestry. 2005. 
Forest health protection emerald ash borer 



home. Newtown Square, PA: U.S. Department of 
Agriculture, Forest Service, Northeastern Area 
State and Private Forestry, http://www.na.fs.fed. 
us/fhp/eab 

18 Stack, R.W.; McBride, D.K.; Lamey, H.A. 1996. 
Dutch elm disease. PP-324 (revised). Fargo, 
ND: North Dakota State Universit}', Cooperative 
Extension Service, http://www.ext.nodak.edu/ 
extpubs/ plantsci/ trees/ pp324w.htm 



18 



Explanation of Calculations of Appendix III 

1 9 Total city carbon emissions were based on 2003 
U.S. per capita carbon emissions, calculated as 
total U.S. carbon emissions (Energy Information 
Administration, 2003, Emissions of Greenhouse 
Gases in the United States 2003. http://www.eia. 
doe.gov/oiaf/l605/l605aold.html) divided by 
2003 total U.S. population (www.census.gov). Per 
capita emissions were multiplied by Minneapolis 
population to estimate total city carbon emissions. 

20 Average passenger automobile emissions per 
mile were based on dividing total 2002 pollutant 
emissions from light-duty gas vehicles (National 
Emission Trends http://www.epa.gov/ttn/chief/ 
trends/index.html) by total miles driven in 2002 by 
passenger cars (National Transportation Statistics 
http://www.bts.gov/publications/national_ 
transportation_statistics/2004/). 

Average annual passenger automobile emissions 
per vehicle were based on dividing total 2002 
pollutant emissions from light-duty gas vehicles 
by total number of passenger cars in 2002 
(National Transportation Statistics http://www. 
bts.gov/publications/national_transportation_ 
statistics/2004/). 

Carbon dioxide emissions from automobiles 
assumed 6 pounds of carbon per gallon of gasoline 
with energy costs of refinement and transportation 
included (Graham, R.L.; Wright, L.L.; Turhollow, 
A.F. 1992. The potential for short-rotation woody 
crops to reduce U.S. CO^ emissions. Climatic 
Change. 22:223-238.) 

21 Average household emissions based on average 
electricity kWh usage, natural gas Btu usage, fuel oil 
Btu usage, kerosene Btu usage, LPG Btu usage, and 
wood Btu usage per household from: 

Energy Information Administration. Total Energy 
Consumption in U.S. Households by Type of 



Housing Unit, 2001 www.eia.doe.gov/emeu/recs/ 
recs200 1 / detailcetbls.html. 

CO^, SO^, and NOx power plant emission per 
KWh from: 

U.S. Environmental Protection Agency. U.S. 
power plant emissions total by year www.epa.gov/ 
cleanenergy/egrid/samples.htm. 

CO emission per kWh assumes one-third of 1 
percent of C emissions is CO based on: 

Energy Information Administration. 1994. 
Energy use and carbon emissions: non-OECD 
countries. DOE/EIA-0579(94). Washington, 
DC: Department of Energy, Energy Information 
Administration, http://tonto.eia.doe.gov/bookshelf 

PMjQ emission per kWh from: 

Layton, M. 2004. 2005 Electricity environmental 
performance report: electricity generation and air 
emissions. Sacramento, CA: California Energy 
Commission. 

http://www.energy.ca.gov/2005_energypolicy/ 
documents/2004- 11-1 5_workshop/2004- 11-1 5_03- 
A_LAYTON.PDF 

CO,, NOx, SO^, PM,Q, and CO emission per Btu 
for natural gas, propane and butane (average used 
to represent LPG), Fuel #4 and #6 (average used to 
represent fuel oil and kerosene) from: 

Abraxas energy consulting. http://www. 
abraxasenergy.com/emissions/ 

CO-, and fine particle emissions per Btu of wood 
from: 

Houck, J.E.; Tiegs, PE.; McCrillis, R.C.; Keithley, 
C; Crouch, J. 1998. Air emissions from residential 
heating: the wood heating option put into 



19 



environmental perspective. In: Proceedings of U.S. 
EPA and Air and Waste Management Association 
conference: living in a global environment, V. 1: 
373-384. 

CO, NOx and SOx emission per Btu of wood based 
on total emissions from wood burning (tonnes) from: 

Residential Wood Burning Emissions in British 
Columbia. 2005. http://www.env.gov.bc.ca/air/ 
airquality/pdfs/wood_emissions.pdf 



Emissions per dry tonne of wood converted to 
emissions per Btu based on average dry weight per 
cord of wood and average Btu per cord from: 

Kuhns, M.; Schmidt, T. 1988. Heating with wood: 
species characteristics and volumes I. NebGuide 
G-88-881-A. Lincoln, NE: University of Nebraska, 
Institute of Agriculture and Natural Resources, 
Cooperative Extension. 



20 



Nowak, David J.; Hoehn, Robert E. Ill, Crane, Daniel E.; Stevens, Jack C; Walton, 
Jeffrey T. 2006. Assessing urban forest effects and values, Minneapolis' 
urban forest. Resour. Bull. NE-166. Newtown Square, PA: U.S. Department of 
Agriculture, Forest Service, Northeastern Research Station. 20 p. 

An analysis of trees in Minneapolis, MN, reveals that the city has about 979,000 
trees with canopies that cover 26.4 percent of the area. The most common tree 
species are green ash, American elm, and boxelder The urban forest currently 
stores about 250,000 tons of carbon valued at $4.6 million. In addition, these 
trees remove about 8,900 tons of carbon per year ($164,000 per year) and trees 
and shrubs combined remove about 384 tons of air pollution per year ($1 .9 
million per year). The structural, or compensatory, value is estimated at $756 
million. Information on the structure and functions of the urban forest can be used 
to improve and augment support for urban forest management programs and 
to integrate urban forests within plans to improve environmental quality in the 
Minneapolis area. 

Keywords: urban forestry; ecosystem services; air pollution removal; carbon 
sequestration; tree value 



Printed on Recycled Paper 



Headquarters of the Northeastern Research Station is in Newtown Square, 
Pennsylvania. Field laboratories are maintained at: 

Amherst, Massachusetts, in cooperation with the University of Massachusetts 
Burlington, Vermont, in cooperation with the University of Vermont 
Delaware, Ohio 

Durham, New Hampshire, In cooperation with the University of New Hampshire 
Hamden, Connecticut, in cooperation with Yale University 
Morgantown, West Virginia, in cooperation with West Virginia University 
Parsons, West Virginia 
Princeton, West Virginia 

Syracuse, New York, in cooperation with the State University of New York, 
College of Environmental Sciences and Forestry at Syracuse University 

Warren, Pennsylvania 



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